Table 1 The feature vector used. The number of measurement has been chosen to be k=10
From: A recursive kinematic random forest and alpha beta filter classifier for 2D radar tracks
Feature | Feature description |
|---|---|
std (Δ i ) | Empirical standard deviation of sample-to-sample distances |
v 1 | |
⋮ | 2-point speed estimate |
v k | |
mean (v i ) | Empirical mean of the speed |
std (v i ) | Empirical standard deviation of the speed |
a 1 | |
⋮ | 2-point acceleration estimate |
a k−1 | |
mean (a i ) | Empirical mean of the acceleration |
std (a i ) | Empirical standard deviation of the acceleration |
mean\((a_{i}^{\perp }) \) | Empirical mean of the normal acceleration |
std\((a_{i}^{\perp }) \) | Empirical standard deviation of the normal acceleration |
|z k −z 0| | Total distance moved |
d 0 | |
⋮ | Distance to coastline |
d k | |
mean (d i ) | Empirical mean of the distance to coast line |